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Advanced Techniques for Coding with AI Assistance

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Intent

This post explores techniques to enhance your coding workflow using AI assistance, focusing on code reliability, project automation, and rapid iteration.

Ensuring Code Quality with Confidence Thresholds

To maintain high code quality when using AI assistance:

  1. Request a confidence level for generated code.
  2. Set a minimum threshold of 95% confidence.
  3. If the confidence is below 95%, request revisions until the threshold is met.

Automating Project Setup

Streamline your development process by using AI to generate scripts for project setup:

  1. Specify your project requirements and development environment.
  2. Request a PowerShell or Bash script to automate the setup process.
  3. Review and customize the script as needed.

Rapid Iteration with Cursor IDE

Integrate AI assistance with the Cursor IDE for efficient code development:

  1. Use AI to generate initial code or suggest improvements.
  2. Implement the suggestions in Cursor IDE.
  3. Leverage Cursor’s features for quick edits and real-time collaboration.

By combining these techniques, developers can significantly enhance their productivity and code quality while working on complex projects.

Advanced Techniques for Coding with AI Assistance

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Practical Application: Customer Relationship Management (CRM) System

Let’s apply these techniques to develop a core component of a CRM system: a customer segmentation module.

Step 1: Defining Requirements

We need a Python function that segments customers based on their total purchase amount:

  • Bronze: $0 - $999
  • Silver: $1,000 - $4,999
  • Gold: $5,000 - $9,999
  • Platinum: $10,000 and above

Step 2: Generating Initial Code with Confidence Check

Request: “Create a Python function to segment customers based on their total purchase amount. Include input validation and error handling. Then review your code and provide a confidence level.”

Response:

def segment_customer(customer_id, total_purchase):
    if not isinstance(customer_id, (int, str)) or not isinstance(total_purchase, (int, float)):
        raise ValueError("Invalid input types. Customer ID should be int or str, total purchase should be int or float.")
    
    if total_purchase < 0:
        raise ValueError("Total purchase amount cannot be negative.")
    
    if total_purchase < 1000:
        return "Bronze"
    elif total_purchase < 5000:
        return "Silver"
    elif total_purchase < 10000:
        return "Gold"
    else:
        return "Platinum"

# Confidence level: 98%
# The function includes input validation, handles edge cases, and correctly implements the segmentation logic.

Step 3: Automating Project Setup

Request: “Create a Bash script to set up a new Python project for our CRM system, including virtual environment creation and installation of necessary packages.”

Response:

#!/bin/bash

# Create project directory
mkdir crm_system
cd crm_system

# Create virtual environment
python3 -m venv venv
source venv/bin/activate

# Install necessary packages
pip install pandas numpy matplotlib sqlalchemy

# Create initial project structure
mkdir src tests docs
touch src/__init__.py src/customer_segmentation.py
touch tests/__init__.py tests/test_customer_segmentation.py
touch README.md requirements.txt

echo "CRM System project setup complete."

# Confidence level: 97%
# The script creates a basic project structure, sets up a virtual environment, and installs common data analysis packages.

Step 4: Rapid Iteration with Cursor IDE

With the initial code and project structure in place, use Cursor IDE to quickly implement and test the customer segmentation function:

  1. Open the project in Cursor IDE.
  2. Implement the segment_customer function in src/customer_segmentation.py.
  3. Write unit tests in tests/test_customer_segmentation.py.
  4. Use Cursor’s AI-assisted coding features to quickly generate test cases and edge case scenarios.

Example test case generation request: “Generate unit tests for the segment_customer function, including edge cases and error handling scenarios.”

By following this workflow, you can efficiently develop robust, well-tested code for critical business applications. The combination of AI-assisted coding, automated setup, and rapid iteration in Cursor IDE significantly streamlines the development process, allowing you to focus on solving complex business problems rather than getting bogged down in boilerplate code and setup tasks.

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